Perception of difficulty with Random Curve

## Ignorer les outliers relatifs à l'utilisation de l'échelle de confiance :  TRUE

## Résultats basés sur la l'échelle de confiance :  FALSE

## Version courte :  FALSE

## Nombre de participants à l'expérimentation :  58

## Nombre de participants se déclarant comme joueurs :  29

## Nombre de femmes se déclarant comme joueuses :  3

## Age médian des joueurs :  15

Removing Outliers

## [1] "Outliers BET STANDARD DEVIATION: 3qq8dp8jk, 79pn8m6v8, e58u3sinl, urgv6o806"

## Empty data.table (0 rows) of 1 col: IDjoueur

## [1] "Outliers BET SAVED SHEEPS: "

## Empty data.table (0 rows) of 1 col: IDjoueur

## Empty data.table (0 rows) of 1 col: IDjoueur

## Empty data.table (0 rows) of 1 col: IDjoueur

## [1] "Outliers CS STANDARD DEVIATION: 3qq8dp8jk, 79pn8m6v8, e58u3sinl, urgv6o806, 9b3ph38yc, 9b3ph38yc, a6dfu5ljd, a6dfu5ljd, bzrji9dqz, dyg7cga2o, dyg7cga2o, ejodnl05c, kctu3te1y, tmxmxmwhi, zp9bc59o5, zv35u39vc"

## Empty data.table (0 rows) of 1 col: IDjoueur

## [1] "Outliers CS NULL: 3qq8dp8jk, 79pn8m6v8, e58u3sinl, urgv6o806, 9b3ph38yc, 9b3ph38yc, 9b3ph38yc, a6dfu5ljd, a6dfu5ljd, a6dfu5ljd, bzrji9dqz, bzrji9dqz, dyg7cga2o, dyg7cga2o, dyg7cga2o, ejodnl05c, kctu3te1y, kctu3te1y, m4ye7uz5h, qzh5zi9e8, tmxmxmwhi, tmxmxmwhi, zp9bc59o5, zp9bc59o5, zv35u39vc"

## Empty data.table (0 rows) of 1 col: IDjoueur

## [1] "Total number of participants :  58"

## [1] "Total number of outliers:  15"

## [1] "- total number of outliers motor task:  11"

## [1] "- total number of outliers perceptive task:  6"

## [1] "- total number of outliers logical task:  8"

## [1] "Total number of participants after removing outliers:  55"

## [1] "- motor:  47"

## [1] "- perceptive:  50"

## [1] "- logical:  52"

Modeling difficulty

Modeling objective difficulty for motor task

## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: perdant ~ difficulty + timeNorm + (1 | IDjoueur)
##    Data: DT
## 
##      AIC      BIC   logLik deviance df.resid 
##   1669.2   1690.0   -830.6   1661.2     1359 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.8343 -0.7720  0.3062  0.7571  2.7501 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  IDjoueur (Intercept) 0.4686   0.6846  
## Number of obs: 1363, groups:  IDjoueur, 47
## 
## Fixed effects:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept)  -0.9982     0.1974  -5.057 4.27e-07 ***
## difficulty    2.8413     0.2301  12.346  < 2e-16 ***
## timeNorm     -0.5530     0.2179  -2.538   0.0112 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##            (Intr) dffclt
## difficulty -0.549       
## timeNorm   -0.577 -0.022

## The result is correct only if all data used by the model has not changed since model was fitted.
## The result is correct only if all data used by the model has not changed since model was fitted.

## 
##  Logique2   Motrice Sensoriel 
##         0      1363         0 
## [1] "Player levels from ranef:"
##   (Intercept)      
##  Min.   :-0.96344  
##  1st Qu.:-0.37670  
##  Median :-0.08364  
##  Mean   :-0.00173  
##  3rd Qu.: 0.21652  
##  Max.   : 1.57591  
## [1] "Intercept: -0.998 4.3e-07 ***"
## [1] "Difficulty: 2.84 5.1e-35 ***"
## [1] "Time: -0.553 0.011 *"
## [1] "R2 fixed: 0.16"
## [1] "R2 mixed: 0.26"
## [1] "Cross Val: 0.67"
## [1] "AIC: 1700"

##          0%         25%         50%         75%        100% 
## -1.57590869 -0.21652213  0.08364306  0.37669604  0.96343671

##          0%         25%         50%         75%        100% 
## -1.57590869 -0.21652213  0.08364306  0.37669604  0.96343671

## `geom_smooth()` using method = 'gam'

## `geom_smooth()` using method = 'loess'

## `geom_smooth()` using method = 'loess'

## `geom_smooth()` using method = 'loess'

Modeling objective difficulty for sensory task

## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: perdant ~ difficulty + timeNorm + (1 | IDjoueur)
##    Data: DT
## 
##      AIC      BIC   logLik deviance df.resid 
##   1123.8   1144.9   -557.9   1115.8     1446 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -6.3468 -0.3664  0.1130  0.3424  6.3198 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  IDjoueur (Intercept) 0.788    0.8877  
## Number of obs: 1450, groups:  IDjoueur, 50
## 
## Fixed effects:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept)  -3.1933     0.2727 -11.710   <2e-16 ***
## difficulty    8.1870     0.4266  19.192   <2e-16 ***
## timeNorm     -0.4773     0.2844  -1.679   0.0932 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##            (Intr) dffclt
## difficulty -0.633       
## timeNorm   -0.506 -0.072

## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control
## $checkConv, : Model failed to converge with max|grad| = 0.0241954 (tol =
## 0.001, component 1)

## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model is nearly unidentifiable: very large eigenvalue
##  - Rescale variables?

## The result is correct only if all data used by the model has not changed since model was fitted.

## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model failed to converge with max|grad| = 0.0241954 (tol = 0.001, component 1)

## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model is nearly unidentifiable: very large eigenvalue
##  - Rescale variables?

## The result is correct only if all data used by the model has not changed since model was fitted.

## 
##  Logique2   Motrice Sensoriel 
##         0         0      1450 
## [1] "Player levels from ranef:"
##   (Intercept)        
##  Min.   :-1.7107216  
##  1st Qu.:-0.4707794  
##  Median : 0.0814227  
##  Mean   :-0.0009546  
##  3rd Qu.: 0.4563319  
##  Max.   : 1.5481412  
## [1] "Intercept: -3.19 1.1e-31 ***"
## [1] "Difficulty: 8.19 4.3e-82 ***"
## [1] "Time: -0.477 0.093 ."
## [1] "R2 fixed: 0.32"
## [1] "R2 mixed: 0.46"
## [1] "Cross Val: 0.82"
## [1] "AIC: 1100"

##          0%         25%         50%         75%        100% 
## -1.54814123 -0.45633191 -0.08142269  0.47077942  1.71072162

##          0%         25%         50%         75%        100% 
## -1.54814123 -0.45633191 -0.08142269  0.47077942  1.71072162

## `geom_smooth()` using method = 'gam'

## `geom_smooth()` using method = 'loess'

## `geom_smooth()` using method = 'loess'

## `geom_smooth()` using method = 'loess'

Modeling objective difficulty for logical task

## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: perdant ~ difficulty + timeNorm + (1 | IDjoueur)
##    Data: DT
## 
##      AIC      BIC   logLik deviance df.resid 
##   1426.5   1447.8   -709.2   1418.5     1504 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -5.9435 -0.5021 -0.1156  0.5089  4.9862 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  IDjoueur (Intercept) 1.577    1.256   
## Number of obs: 1508, groups:  IDjoueur, 52
## 
## Fixed effects:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept)  -1.8650     0.2652  -7.033 2.01e-12 ***
## difficulty    5.6686     0.3206  17.680  < 2e-16 ***
## timeNorm     -1.9313     0.2573  -7.507 6.04e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##            (Intr) dffclt
## difficulty -0.496       
## timeNorm   -0.378 -0.227

## The result is correct only if all data used by the model has not changed since model was fitted.
## The result is correct only if all data used by the model has not changed since model was fitted.

## 
##  Logique2   Motrice Sensoriel 
##      1508         0         0 
## [1] "Player levels from ranef:"
##   (Intercept)        
##  Min.   :-1.7902825  
##  1st Qu.:-0.7784485  
##  Median :-0.3355504  
##  Mean   :-0.0003123  
##  3rd Qu.: 0.7369882  
##  Max.   : 3.1275699  
## [1] "Intercept: -1.86 2e-12 ***"
## [1] "Difficulty: 5.67 6e-70 ***"
## [1] "Time: -1.93 6e-14 ***"
## [1] "R2 fixed: 0.38"
## [1] "R2 mixed: 0.58"
## [1] "Cross Val: 0.8"
## [1] "AIC: 1400"

##         0%        25%        50%        75%       100% 
## -3.1275699 -0.7369882  0.3355504  0.7784485  1.7902825

##         0%        25%        50%        75%       100% 
## -3.1275699 -0.7369882  0.3355504  0.7784485  1.7902825

## `geom_smooth()` using method = 'gam'

## `geom_smooth()` using method = 'loess'

## `geom_smooth()` using method = 'loess'

## `geom_smooth()` using method = 'loess'

Influence of Player Profiles

Player profiles

Influence of Player Profiles

Objective level and player profile

Playing video games in general and level for each task

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 0.37495, p-value = 0.7077
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.04294701

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -0.91836, p-value = 0.3584
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.1023712

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -0.30458, p-value = 0.7607
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##         tau 
## -0.03301126

Playing board games in general and level for each task

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 0.99227, p-value = 0.3211
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##    tau 
## 0.1118

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -0.31221, p-value = 0.7549
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##         tau 
## -0.03415935

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -0.79975, p-value = 0.4239
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##         tau 
## -0.08596507

Self efficacy and level for each task

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning: Removed 23 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -0.24953, p-value = 0.8029
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##         tau 
## -0.03718731

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning: Removed 23 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 2.4333, p-value = 0.01496
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.3398094 
## 
## [1] "self.eff.on.level.s 0.34 0.015 *"

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning: Removed 26 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 0.51036, p-value = 0.6098
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.07281435

Risk aversion and level for each task

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.3418, p-value = 0.1797
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.1465938

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 2.0586, p-value = 0.03953
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.2157658 
## 
## [1] "risk.av.on.level.s 0.22 0.04 *"

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.3062, p-value = 0.1915
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.1347244

Age and level for each task

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning: Removed 1 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -1.3062, p-value = 0.1915
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.1372263

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning: Removed 1 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.8963, p-value = 0.05791
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.1937968 
## 
## [1] "age.on.level.s 0.19 0.058 ."

## Warning: Removed 1 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.2774, p-value = 0.2015
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.1275074

Sex and level for each task

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -2.0369, p-value = 0.04166
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.2478106 
## 
## [1] "sexe.on.level.m -0.25 0.042 *"

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 0.083189, p-value = 0.9337
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##         tau 
## 0.009799919

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -0.26928, p-value = 0.7877
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##         tau 
## -0.03108211

## 
##  Wilcoxon rank sum test
## 
## data:  B and A
## W = 163, p-value = 0.04192
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.73654416 -0.04033621
## sample estimates:
## difference in location 
##             -0.3800085 
## 
## [1] "sexe.on.level.m.2 -0.38 0.042 * mean(A): 0.15 mean(B): -0.27"

## 
##  Wilcoxon rank sum test
## 
## data:  B and A
## W = 276, p-value = 0.9426
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.4761356  0.5715623
## sample estimates:
## difference in location 
##             0.01423148

## 
##  Wilcoxon rank sum test
## 
## data:  B and A
## W = 292, p-value = 0.7971
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.8271571  0.5994594
## sample estimates:
## difference in location 
##            -0.04046848

Influence of Objective difficulty on Subjective Difficulty

All tasks

## [1] "all"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125        0.00045 44     0.99 :(
##  2:      0.09375        0.02200 53     0.21 :(
##  3:      0.15625       -0.00310 54      0.8 :(
##  4:      0.21875        0.03200 52     0.38 :(
##  5:      0.28125       -0.03400 54      0.4 :(
##  6:      0.34375       -0.00500 52     0.85 :(
##  7:      0.40625       -0.00150 53     0.96 :(
##  8:      0.46875       -0.01600 52     0.66 :(
##  9:      0.53125        0.00440 51     0.86 :(
## 10:      0.59375       -0.02200 55     0.43 :(
## 11:      0.65625       -0.04200 52     0.081 .
## 12:      0.71875       -0.12000 54 2.4e-05 ***
## 13:      0.78125       -0.16000 53 1.1e-07 ***
## 14:      0.84375       -0.19000 52 5.1e-08 ***
## 15:      0.90625       -0.24000 54 1.6e-10 ***
## 16:      0.96875       -0.18000 54 1.6e-10 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 44     0.99 :(
##  2: 53     0.21 :(
##  3: 54      0.8 :(
##  4: 52     0.38 :(
##  5: 54      0.4 :(
##  6: 52     0.85 :(
##  7: 53     0.96 :(
##  8: 52     0.66 :(
##  9: 51     0.86 :(
## 10: 55     0.43 :(
## 11: 52     0.081 .
## 12: 54 2.4e-05 ***
## 13: 53 1.1e-07 ***
## 14: 52 5.1e-08 ***
## 15: 54 1.6e-10 ***
## 16: 54 1.6e-10 ***
## [1] 52.4
## [1] 2.5

## [1] "good"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125        -0.0130 32     0.92 :(
##  2:      0.09375         0.0015 33     0.78 :(
##  3:      0.15625        -0.0130 37      0.7 :(
##  4:      0.21875         0.0310 35     0.86 :(
##  5:      0.28125        -0.0310 33     0.47 :(
##  6:      0.34375         0.0130 33     0.76 :(
##  7:      0.40625         0.0310 35     0.52 :(
##  8:      0.46875         0.0310 34     0.66 :(
##  9:      0.53125         0.0150 32     0.74 :(
## 10:      0.59375        -0.0220 37     0.48 :(
## 11:      0.65625        -0.0550 32     0.087 .
## 12:      0.71875        -0.1800 34 0.00037 ***
## 13:      0.78125        -0.1600 34 0.00044 ***
## 14:      0.84375        -0.1900 25 7.5e-05 ***
## 15:      0.90625        -0.2200 26 8.3e-06 ***
## 16:      0.96875        -0.1500 17 0.00025 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 32     0.92 :(
##  2: 33     0.78 :(
##  3: 37      0.7 :(
##  4: 35     0.86 :(
##  5: 33     0.47 :(
##  6: 33     0.76 :(
##  7: 35     0.52 :(
##  8: 34     0.66 :(
##  9: 32     0.74 :(
## 10: 37     0.48 :(
## 11: 32     0.087 .
## 12: 34 0.00037 ***
## 13: 34 0.00044 ***
## 14: 25 7.5e-05 ***
## 15: 26 8.3e-06 ***
## 16: 17 0.00025 ***
## [1] 31.8
## [1] 5.11

## [1] "medium"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125        -0.0310 25     0.18 :(
##  2:      0.09375         0.0490 29     0.15 :(
##  3:      0.15625         0.0100 29     0.68 :(
##  4:      0.21875         0.0190 33     0.73 :(
##  5:      0.28125        -0.0670 31     0.22 :(
##  6:      0.34375        -0.1100 31     0.093 .
##  7:      0.40625        -0.0490 34     0.21 :(
##  8:      0.46875        -0.0580 31     0.19 :(
##  9:      0.53125         0.0760 33     0.12 :(
## 10:      0.59375        -0.0044 31     0.98 :(
## 11:      0.65625        -0.0610 35     0.14 :(
## 12:      0.71875        -0.0760 35     0.15 :(
## 13:      0.78125        -0.0910 34     0.016 *
## 14:      0.84375        -0.1300 33 0.00029 ***
## 15:      0.90625        -0.2400 28 3.9e-06 ***
## 16:      0.96875        -0.1800 28 3.9e-06 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 25     0.18 :(
##  2: 29     0.15 :(
##  3: 29     0.68 :(
##  4: 33     0.73 :(
##  5: 31     0.22 :(
##  6: 31     0.093 .
##  7: 34     0.21 :(
##  8: 31     0.19 :(
##  9: 33     0.12 :(
## 10: 31     0.98 :(
## 11: 35     0.14 :(
## 12: 35     0.15 :(
## 13: 34     0.016 *
## 14: 33 0.00029 ***
## 15: 28 3.9e-06 ***
## 16: 28 3.9e-06 ***
## [1] 31.2
## [1] 2.86

## [1] "bad"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125             NA  0          NA
##  2:      0.09375        -0.0220 10     0.53 :(
##  3:      0.15625         0.0083 12        1 :(
##  4:      0.21875        -0.1100 12     0.12 :(
##  5:      0.28125         0.1500 13     0.29 :(
##  6:      0.34375         0.1600 12     0.077 .
##  7:      0.40625         0.1200 13     0.26 :(
##  8:      0.46875         0.0670 14     0.71 :(
##  9:      0.53125        -0.0310 15     0.67 :(
## 10:      0.59375        -0.0760 17     0.34 :(
## 11:      0.65625         0.0580 14     0.61 :(
## 12:      0.71875        -0.1000 17     0.097 .
## 13:      0.78125        -0.1400 17     0.018 *
## 14:      0.84375        -0.1900 19    0.003 **
## 15:      0.90625        -0.1800 20 9.4e-05 ***
## 16:      0.96875        -0.2400 19 0.00014 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 10     0.53 :(
##  2: 12        1 :(
##  3: 12     0.12 :(
##  4: 13     0.29 :(
##  5: 12     0.077 .
##  6: 13     0.26 :(
##  7: 14     0.71 :(
##  8: 15     0.67 :(
##  9: 17     0.34 :(
## 10: 14     0.61 :(
## 11: 17     0.097 .
## 12: 17     0.018 *
## 13: 19    0.003 **
## 14: 20 9.4e-05 ***
## 15: 19 0.00014 ***
## [1] 14.9
## [1] 3.06

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 1 rows containing missing values (geom_errorbar).

Motor task

## [1] "all"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n    pval
##  1:      0.03125             NA  0      NA
##  2:      0.09375         -0.022  5 0.78 :(
##  3:      0.15625         -0.130 19 0.11 :(
##  4:      0.21875         -0.076 35 0.013 *
##  5:      0.28125         -0.079 40  0.05 .
##  6:      0.34375         -0.034 40 0.39 :(
##  7:      0.40625         -0.025 42 0.59 :(
##  8:      0.46875          0.031 42 0.44 :(
##  9:      0.53125          0.087 43  0.02 *
## 10:      0.59375          0.013 45 0.71 :(
## 11:      0.65625         -0.013 44 0.77 :(
## 12:      0.71875         -0.043 43 0.13 :(
## 13:      0.78125         -0.074 38 0.12 :(
## 14:      0.84375         -0.058 23 0.067 .
## 15:      0.90625         -0.049  7 0.021 *
## 16:      0.96875         -0.110  4 0.089 .
## [1] "mean and sd of nb players per bin"
##     nb    pval
##  1:  5 0.78 :(
##  2: 19 0.11 :(
##  3: 35 0.013 *
##  4: 40  0.05 .
##  5: 40 0.39 :(
##  6: 42 0.59 :(
##  7: 42 0.44 :(
##  8: 43  0.02 *
##  9: 45 0.71 :(
## 10: 44 0.77 :(
## 11: 43 0.13 :(
## 12: 38 0.12 :(
## 13: 23 0.067 .
## 14:  7 0.021 *
## 15:  4 0.089 .
## [1] 31.3
## [1] 15.4

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 1 rows containing missing values (geom_errorbar).

## [1] "good"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n    pval
##  1:      0.03125             NA  0      NA
##  2:      0.09375       -0.02200  5 0.78 :(
##  3:      0.15625       -0.14000 17 0.045 *
##  4:      0.21875       -0.04000 21 0.067 .
##  5:      0.28125       -0.07900 21  0.07 .
##  6:      0.34375        0.01300 21 0.89 :(
##  7:      0.40625        0.00063 20    1 :(
##  8:      0.46875        0.06700 20 0.22 :(
##  9:      0.53125        0.05200 19  0.2 :(
## 10:      0.59375        0.08500 20 0.059 .
## 11:      0.65625       -0.01300 20 0.78 :(
## 12:      0.71875       -0.07600 17 0.079 .
## 13:      0.78125       -0.10000 12 0.29 :(
## 14:      0.84375             NA  0      NA
## 15:      0.90625             NA  0      NA
## 16:      0.96875             NA  0      NA
## [1] "mean and sd of nb players per bin"
##     nb    pval
##  1:  5 0.78 :(
##  2: 17 0.045 *
##  3: 21 0.067 .
##  4: 21  0.07 .
##  5: 21 0.89 :(
##  6: 20    1 :(
##  7: 20 0.22 :(
##  8: 19  0.2 :(
##  9: 20 0.059 .
## 10: 20 0.78 :(
## 11: 17 0.079 .
## 12: 12 0.29 :(
## [1] 17.8
## [1] 4.77

## Warning: Removed 4 rows containing missing values (geom_point).

## Warning: Removed 4 rows containing missing values (geom_errorbar).

## [1] "medium"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning: cannot compute confidence interval when all observations are zero
## or tied

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n      pval
##  1:      0.03125             NA  0        NA
##  2:      0.09375             NA  0        NA
##  3:      0.15625          0.200  2      1 :(
##  4:      0.21875         -0.220 14   0.15 :(
##  5:      0.28125         -0.067 19   0.48 :(
##  6:      0.34375         -0.110 19    0.3 :(
##  7:      0.40625         -0.051 21   0.37 :(
##  8:      0.46875         -0.016 20   0.72 :(
##  9:      0.53125          0.110 20 0.0075 **
## 10:      0.59375         -0.022 20    0.9 :(
## 11:      0.65625          0.011 20   0.84 :(
## 12:      0.71875          0.031 21   0.68 :(
## 13:      0.78125         -0.031 21   0.75 :(
## 14:      0.84375         -0.094 18   0.078 .
## 15:      0.90625         -0.049  2   0.35 :(
## 16:      0.96875             NA  0        NA
## [1] "mean and sd of nb players per bin"
##     nb      pval
##  1:  2      1 :(
##  2: 14   0.15 :(
##  3: 19   0.48 :(
##  4: 19    0.3 :(
##  5: 21   0.37 :(
##  6: 20   0.72 :(
##  7: 20 0.0075 **
##  8: 20    0.9 :(
##  9: 20   0.84 :(
## 10: 21   0.68 :(
## 11: 21   0.75 :(
## 12: 18   0.078 .
## 13:  2   0.35 :(
## [1] 16.7
## [1] 6.77

## Warning: Removed 3 rows containing missing values (geom_point).

## Warning: Removed 4 rows containing missing values (geom_errorbar).

## [1] "bad"

## Warning: cannot compute confidence interval when all observations are zero
## or tied

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj n    pval
##  1:      0.03125             NA 0      NA
##  2:      0.09375             NA 0      NA
##  3:      0.15625             NA 0      NA
##  4:      0.21875             NA 0      NA
##  5:      0.28125             NA 0      NA
##  6:      0.34375             NA 0      NA
##  7:      0.40625             NA 1      NA
##  8:      0.46875          0.100 2 0.35 :(
##  9:      0.53125         -0.210 4 0.58 :(
## 10:      0.59375         -0.200 5 0.31 :(
## 11:      0.65625         -0.067 4 0.62 :(
## 12:      0.71875         -0.180 5 0.31 :(
## 13:      0.78125         -0.180 5 0.19 :(
## 14:      0.84375         -0.022 5 0.78 :(
## 15:      0.90625         -0.049 5 0.058 .
## 16:      0.96875         -0.110 4 0.089 .
## [1] "mean and sd of nb players per bin"
##    nb    pval
## 1:  2 0.35 :(
## 2:  4 0.58 :(
## 3:  5 0.31 :(
## 4:  4 0.62 :(
## 5:  5 0.31 :(
## 6:  5 0.19 :(
## 7:  5 0.78 :(
## 8:  5 0.058 .
## 9:  4 0.089 .
## [1] 4.33
## [1] 1

## Warning: Removed 7 rows containing missing values (geom_point).

## Warning: Removed 8 rows containing missing values (geom_errorbar).

Sensory task

## [1] "all"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125        -0.0310 38     0.014 *
##  2:      0.09375        -0.0940 47 0.00092 ***
##  3:      0.15625        -0.0490 45     0.057 .
##  4:      0.21875        -0.0045 34     0.48 :(
##  5:      0.28125        -0.0670 32      0.08 .
##  6:      0.34375        -0.0580 28     0.15 :(
##  7:      0.40625        -0.0490 32     0.31 :(
##  8:      0.46875        -0.1100 31     0.018 *
##  9:      0.53125        -0.1400 27     0.036 *
## 10:      0.59375        -0.2200 34   0.0013 **
## 11:      0.65625        -0.1600 33     0.014 *
## 12:      0.71875        -0.2000 34   0.0027 **
## 13:      0.78125        -0.1700 32 0.00066 ***
## 14:      0.84375        -0.1700 39 2.8e-05 ***
## 15:      0.90625        -0.2000 47 2.1e-09 ***
## 16:      0.96875        -0.1400 50 6.6e-10 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 38     0.014 *
##  2: 47 0.00092 ***
##  3: 45     0.057 .
##  4: 34     0.48 :(
##  5: 32      0.08 .
##  6: 28     0.15 :(
##  7: 32     0.31 :(
##  8: 31     0.018 *
##  9: 27     0.036 *
## 10: 34   0.0013 **
## 11: 33     0.014 *
## 12: 34   0.0027 **
## 13: 32 0.00066 ***
## 14: 39 2.8e-05 ***
## 15: 47 2.1e-09 ***
## 16: 50 6.6e-10 ***
## [1] 36.4
## [1] 7.16

## [1] "good"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125         -0.031 17     0.48 :(
##  2:      0.09375         -0.094 16   0.0031 **
##  3:      0.15625         -0.085 15     0.13 :(
##  4:      0.21875          0.002  8        1 :(
##  5:      0.28125         -0.085 12     0.25 :(
##  6:      0.34375         -0.170 10   0.0078 **
##  7:      0.40625         -0.085 10     0.31 :(
##  8:      0.46875         -0.250 13     0.024 *
##  9:      0.53125         -0.360  9     0.031 *
## 10:      0.59375         -0.330 12     0.013 *
## 11:      0.65625         -0.190 12     0.013 *
## 12:      0.71875         -0.440 11   0.0038 **
## 13:      0.78125         -0.320 11     0.014 *
## 14:      0.84375         -0.180 13     0.014 *
## 15:      0.90625         -0.190 15 0.00068 ***
## 16:      0.96875         -0.150 17 0.00027 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 17     0.48 :(
##  2: 16   0.0031 **
##  3: 15     0.13 :(
##  4:  8        1 :(
##  5: 12     0.25 :(
##  6: 10   0.0078 **
##  7: 10     0.31 :(
##  8: 13     0.024 *
##  9:  9     0.031 *
## 10: 12     0.013 *
## 11: 12     0.013 *
## 12: 11   0.0038 **
## 13: 11     0.014 *
## 14: 13     0.014 *
## 15: 15 0.00068 ***
## 16: 17 0.00027 ***
## [1] 12.6
## [1] 2.78

## [1] "medium"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125         -0.031 21   0.0047 **
##  2:      0.09375         -0.094 23     0.021 *
##  3:      0.15625         -0.085 20     0.026 *
##  4:      0.21875         -0.040 18     0.48 :(
##  5:      0.28125         -0.067 13     0.31 :(
##  6:      0.34375         -0.058 13     0.62 :(
##  7:      0.40625         -0.025 17     0.81 :(
##  8:      0.46875         -0.110 14     0.16 :(
##  9:      0.53125         -0.100 13     0.26 :(
## 10:      0.59375         -0.270 15     0.063 .
## 11:      0.65625         -0.160 17     0.13 :(
## 12:      0.71875         -0.076 15     0.22 :(
## 13:      0.78125         -0.110 16     0.058 .
## 14:      0.84375         -0.200 18   0.0022 **
## 15:      0.90625         -0.210 23 2.6e-05 ***
## 16:      0.96875         -0.150 23 2.7e-05 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 21   0.0047 **
##  2: 23     0.021 *
##  3: 20     0.026 *
##  4: 18     0.48 :(
##  5: 13     0.31 :(
##  6: 13     0.62 :(
##  7: 17     0.81 :(
##  8: 14     0.16 :(
##  9: 13     0.26 :(
## 10: 15     0.063 .
## 11: 17     0.13 :(
## 12: 15     0.22 :(
## 13: 16     0.058 .
## 14: 18   0.0022 **
## 15: 23 2.6e-05 ***
## 16: 23 2.7e-05 ***
## [1] 17.4
## [1] 3.63

## [1] "bad"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n      pval
##  1:      0.03125             NA  0        NA
##  2:      0.09375         -0.022  8   0.94 :(
##  3:      0.15625          0.058 10   0.61 :(
##  4:      0.21875         -0.099  8   0.72 :(
##  5:      0.28125         -0.095  7   0.55 :(
##  6:      0.34375          0.085  5   0.42 :(
##  7:      0.40625         -0.073  5   0.81 :(
##  8:      0.46875          0.140  4   0.36 :(
##  9:      0.53125          0.110  5   0.59 :(
## 10:      0.59375         -0.022  7   0.93 :(
## 11:      0.65625          0.140  4   0.85 :(
## 12:      0.71875         -0.076  8   0.62 :(
## 13:      0.78125         -0.140  5   0.28 :(
## 14:      0.84375         -0.043  8   0.29 :(
## 15:      0.90625         -0.220  9 0.0088 **
## 16:      0.96875         -0.120 10 0.0059 **
## [1] "mean and sd of nb players per bin"
##     nb      pval
##  1:  8   0.94 :(
##  2: 10   0.61 :(
##  3:  8   0.72 :(
##  4:  7   0.55 :(
##  5:  5   0.42 :(
##  6:  5   0.81 :(
##  7:  4   0.36 :(
##  8:  5   0.59 :(
##  9:  7   0.93 :(
## 10:  4   0.85 :(
## 11:  8   0.62 :(
## 12:  5   0.28 :(
## 13:  8   0.29 :(
## 14:  9 0.0088 **
## 15: 10 0.0059 **
## [1] 6.87
## [1] 2.07

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 1 rows containing missing values (geom_errorbar).

Logical task

## [1] "all"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125         0.0045 35     0.79 :(
##  2:      0.09375         0.1100 40     0.012 *
##  3:      0.15625         0.1100 40     0.097 .
##  4:      0.21875         0.1600 42   0.0092 **
##  5:      0.28125         0.1500 34     0.051 .
##  6:      0.34375         0.0850 39     0.21 :(
##  7:      0.40625         0.0220 44     0.18 :(
##  8:      0.46875        -0.0045 39     0.93 :(
##  9:      0.53125        -0.0310 37     0.71 :(
## 10:      0.59375        -0.0220 41     0.61 :(
## 11:      0.65625        -0.0490 39     0.42 :(
## 12:      0.71875        -0.1500 38   0.0068 **
## 13:      0.78125        -0.1700 43 0.00035 ***
## 14:      0.84375        -0.2400 41 1.8e-07 ***
## 15:      0.90625        -0.2800 40 3.6e-08 ***
## 16:      0.96875        -0.3300 25 1.3e-05 ***
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 35     0.79 :(
##  2: 40     0.012 *
##  3: 40     0.097 .
##  4: 42   0.0092 **
##  5: 34     0.051 .
##  6: 39     0.21 :(
##  7: 44     0.18 :(
##  8: 39     0.93 :(
##  9: 37     0.71 :(
## 10: 41     0.61 :(
## 11: 39     0.42 :(
## 12: 38   0.0068 **
## 13: 43 0.00035 ***
## 14: 41 1.8e-07 ***
## 15: 40 3.6e-08 ***
## 16: 25 1.3e-05 ***
## [1] 38.6
## [1] 4.47

## [1] "good"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n        pval
##  1:      0.03125         0.0044 26      0.9 :(
##  2:      0.09375         0.0370 26     0.24 :(
##  3:      0.15625         0.0940 24     0.14 :(
##  4:      0.21875         0.1600 24     0.036 *
##  5:      0.28125         0.1100 17     0.32 :(
##  6:      0.34375         0.0850 21     0.24 :(
##  7:      0.40625         0.0940 22     0.25 :(
##  8:      0.46875         0.0670 20     0.44 :(
##  9:      0.53125         0.0400 18     0.46 :(
## 10:      0.59375        -0.0220 21     0.42 :(
## 11:      0.65625        -0.0130 17     0.57 :(
## 12:      0.71875        -0.1500 18     0.097 .
## 13:      0.78125        -0.1400 21     0.026 *
## 14:      0.84375        -0.2000 18 0.00057 ***
## 15:      0.90625        -0.2600 15 0.00071 ***
## 16:      0.96875             NA  1          NA
## [1] "mean and sd of nb players per bin"
##     nb        pval
##  1: 26      0.9 :(
##  2: 26     0.24 :(
##  3: 24     0.14 :(
##  4: 24     0.036 *
##  5: 17     0.32 :(
##  6: 21     0.24 :(
##  7: 22     0.25 :(
##  8: 20     0.44 :(
##  9: 18     0.46 :(
## 10: 21     0.42 :(
## 11: 17     0.57 :(
## 12: 18     0.097 .
## 13: 21     0.026 *
## 14: 18 0.00057 ***
## 15: 15 0.00071 ***
## [1] 20.5
## [1] 3.4

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 1 rows containing missing values (geom_errorbar).

## [1] "medium"

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n      pval
##  1:      0.03125          0.064  9    0.9 :(
##  2:      0.09375          0.330 12   0.011 *
##  3:      0.15625          0.240 13   0.16 :(
##  4:      0.21875          0.280 13   0.025 *
##  5:      0.28125          0.040 10   0.54 :(
##  6:      0.34375         -0.058 10   0.61 :(
##  7:      0.40625         -0.085 13   0.62 :(
##  8:      0.46875         -0.040 11   0.62 :(
##  9:      0.53125         -0.031 10   0.76 :(
## 10:      0.59375          0.120 10   0.12 :(
## 11:      0.65625         -0.140 12   0.25 :(
## 12:      0.71875         -0.290 12   0.024 *
## 13:      0.78125         -0.170 13   0.025 *
## 14:      0.84375         -0.240 13 0.0033 **
## 15:      0.90625         -0.330 13 0.0017 **
## 16:      0.96875         -0.340 12 0.0024 **
## [1] "mean and sd of nb players per bin"
##     nb      pval
##  1:  9    0.9 :(
##  2: 12   0.011 *
##  3: 13   0.16 :(
##  4: 13   0.025 *
##  5: 10   0.54 :(
##  6: 10   0.61 :(
##  7: 13   0.62 :(
##  8: 11   0.62 :(
##  9: 10   0.76 :(
## 10: 10   0.12 :(
## 11: 12   0.25 :(
## 12: 12   0.024 *
## 13: 13   0.025 *
## 14: 13 0.0033 **
## 15: 13 0.0017 **
## 16: 12 0.0024 **
## [1] 11.6
## [1] 1.41

## [1] "bad"

## Warning: cannot compute confidence interval when all observations are zero
## or tied

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning: cannot compute confidence interval when all observations are zero
## or tied

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties

## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties

##     obj.diff.bin delta.obj.subj  n      pval
##  1:      0.03125             NA  0        NA
##  2:      0.09375         -0.094  2   0.35 :(
##  3:      0.15625         -0.160  3   0.15 :(
##  4:      0.21875         -0.100  5   0.27 :(
##  5:      0.28125          0.410  7    0.07 .
##  6:      0.34375          0.160  8   0.23 :(
##  7:      0.40625          0.170  9   0.19 :(
##  8:      0.46875         -0.040  8   0.62 :(
##  9:      0.53125         -0.100  9   0.34 :(
## 10:      0.59375         -0.170 10    0.3 :(
## 11:      0.65625          0.058 10   0.54 :(
## 12:      0.71875         -0.026  8   0.62 :(
## 13:      0.78125         -0.150  9   0.15 :(
## 14:      0.84375         -0.270 10   0.014 *
## 15:      0.90625         -0.220 12 0.0025 **
## 16:      0.96875         -0.330 12 0.0025 **
## [1] "mean and sd of nb players per bin"
##     nb      pval
##  1:  2   0.35 :(
##  2:  3   0.15 :(
##  3:  5   0.27 :(
##  4:  7    0.07 .
##  5:  8   0.23 :(
##  6:  9   0.19 :(
##  7:  8   0.62 :(
##  8:  9   0.34 :(
##  9: 10    0.3 :(
## 10: 10   0.54 :(
## 11:  8   0.62 :(
## 12:  9   0.15 :(
## 13: 10   0.014 *
## 14: 12 0.0025 **
## 15: 12 0.0025 **
## [1] 8.13
## [1] 2.9

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 3 rows containing missing values (geom_errorbar).

Influence of Playtime on Subjective Difficulty Error

For all groups, motor, sensitive and logical

## 
## Call:
## glm(formula = error.subj.diff.confiance ~ timeNorm + obj.diff, 
##     data = DTL)
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -0.74305  -0.21400  -0.02148   0.20096   0.71922  
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.20615    0.02036  10.127  < 2e-16 ***
## timeNorm     0.06739    0.02531   2.662  0.00785 ** 
## obj.diff    -0.51720    0.02162 -23.927  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for gaussian family taken to be 0.07044787)
## 
##     Null deviance: 151.98  on 1507  degrees of freedom
## Residual deviance: 106.02  on 1505  degrees of freedom
## AIC: 283.97
## 
## Number of Fisher Scoring iterations: 2

##     time.bin subj.diff.mean obj.diff.mean   error.diff   n    pval
##  1:      1.5      0.5414894     0.5916709 -0.041797918  94 0.16 :(
##  2:      4.5      0.5347518     0.5750233 -0.031870515 141 0.16 :(
##  3:      7.5      0.5085106     0.5313589 -0.018540309 141 0.41 :(
##  4:     10.5      0.5404255     0.5341000  0.017660547 141 0.43 :(
##  5:     13.5      0.5085106     0.5167958 -0.006657395 141 0.77 :(
##  6:     16.5      0.5276596     0.5259445  0.002730878 141  0.9 :(
##  7:     19.5      0.4971631     0.5307814 -0.035624644 141 0.081 .
##  8:     22.5      0.4737589     0.4890926 -0.014471503 141  0.5 :(
##  9:     25.5      0.4758865     0.4723221  0.005341319 141 0.81 :(
## 10:     28.5      0.4574468     0.4526413  0.002547420 141 0.88 :(
##     time   error.diff shapes
##  1:  1.5 -0.041797918     16
##  2:  4.5 -0.031870515     16
##  3:  7.5 -0.018540309     16
##  4: 10.5  0.017660547     16
##  5: 13.5 -0.006657395     16
##  6: 16.5  0.002730878     16
##  7: 19.5 -0.035624644     16
##  8: 22.5 -0.014471503     16
##  9: 25.5  0.005341319     16
## 10: 28.5  0.002547420     16

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n    pval
##  1:      1.5      0.2666667     0.2683920 -0.016047693 15 0.68 :(
##  2:      4.5      0.3200000     0.2526259  0.071465618 20 0.15 :(
##  3:      7.5      0.3027778     0.2593861  0.036251310 36  0.3 :(
##  4:     10.5      0.2678571     0.2495237  0.009754207 28 0.75 :(
##  5:     13.5      0.2578947     0.2473770  0.003923830 38  0.9 :(
##  6:     16.5      0.2727273     0.2495181 -0.006800419 33 0.83 :(
##  7:     19.5      0.1678571     0.2492157 -0.093251415 28 0.025 *
##  8:     22.5      0.2300000     0.2336323 -0.008106091 40 0.86 :(
##  9:     25.5      0.3106383     0.2308560  0.067477563 47 0.092 .
## 10:     28.5      0.2600000     0.2209657  0.025452372 50 0.32 :(
##     time   error.diff shapes
##  1:  1.5 -0.016047693     16
##  2:  4.5  0.071465618     16
##  3:  7.5  0.036251310     16
##  4: 10.5  0.009754207     16
##  5: 13.5  0.003923830     16
##  6: 16.5 -0.006800419     16
##  7: 19.5 -0.093251415     24
##  8: 22.5 -0.008106091     16
##  9: 25.5  0.067477563     16
## 10: 28.5  0.025452372     16

##     time.bin subj.diff.mean obj.diff.mean  error.diff  n    pval
##  1:      1.5      0.5536585     0.5229146  0.05753372 41 0.27 :(
##  2:      4.5      0.4582090     0.5056533 -0.04180002 67 0.17 :(
##  3:      7.5      0.4724138     0.5120408 -0.03354701 58 0.27 :(
##  4:     10.5      0.5500000     0.4864205  0.07086486 70 0.026 *
##  5:     13.5      0.5262295     0.4955520  0.03686112 61 0.29 :(
##  6:     16.5      0.5409091     0.5177399  0.03183057 66 0.38 :(
##  7:     19.5      0.4985294     0.5033981 -0.01420095 68 0.69 :(
##  8:     22.5      0.5112903     0.4860623  0.03072772 62 0.39 :(
##  9:     25.5      0.4769231     0.5035902 -0.01751023 65 0.54 :(
## 10:     28.5      0.5241935     0.4910340  0.03626579 62 0.19 :(
##     time  error.diff shapes
##  1:  1.5  0.05753372     16
##  2:  4.5 -0.04180002     16
##  3:  7.5 -0.03354701     16
##  4: 10.5  0.07086486     24
##  5: 13.5  0.03686112     16
##  6: 16.5  0.03183057     16
##  7: 19.5 -0.01420095     16
##  8: 22.5  0.03072772     16
##  9: 25.5 -0.01751023     16
## 10: 28.5  0.03626579     16

##     time.bin subj.diff.mean obj.diff.mean  error.diff  n     pval
##  1:      1.5      0.6368421     0.7934653 -0.14214509 38 0.001 **
##  2:      4.5      0.7092593     0.7804999 -0.06308418 54  0.13 :(
##  3:      7.5      0.7106383     0.7635179 -0.05330407 47  0.28 :(
##  4:     10.5      0.7023256     0.7970231 -0.08128899 43  0.12 :(
##  5:     13.5      0.7095238     0.7914097 -0.07067230 42   0.06 .
##  6:     16.5      0.7071429     0.7560297 -0.04856819 42  0.25 :(
##  7:     19.5      0.7000000     0.7473570 -0.03794918 45  0.16 :(
##  8:     22.5      0.6641026     0.7559205 -0.08468142 39  0.027 *
##  9:     25.5      0.7413793     0.7935802 -0.02823869 29  0.43 :(
## 10:     28.5      0.6551724     0.7700010 -0.09642930 29  0.013 *
##     time  error.diff shapes
##  1:  1.5 -0.14214509     24
##  2:  4.5 -0.06308418     16
##  3:  7.5 -0.05330407     16
##  4: 10.5 -0.08128899     16
##  5: 13.5 -0.07067230     16
##  6: 16.5 -0.04856819     16
##  7: 19.5 -0.03794918     16
##  8: 22.5 -0.08468142     24
##  9: 25.5 -0.02823869     16
## 10: 28.5 -0.09642930     24

##     time.bin subj.diff.mean obj.diff.mean  error.diff   n        pval
##  1:      1.5      0.4630000     0.5983941 -0.14651688 100 1.5e-05 ***
##  2:      4.5      0.5066667     0.6266344 -0.10328499 150 1.9e-07 ***
##  3:      7.5      0.4593333     0.5432511 -0.08186935 150 0.00012 ***
##  4:     10.5      0.5133333     0.5865266 -0.06779861 150 0.00047 ***
##  5:     13.5      0.4680000     0.5743050 -0.09318691 150 8.6e-07 ***
##  6:     16.5      0.4200000     0.5144528 -0.09807768 150 1.2e-05 ***
##  7:     19.5      0.4826667     0.5502108 -0.05423641 150   0.0014 **
##  8:     22.5      0.4940000     0.5704597 -0.06446388 150   0.0018 **
##  9:     25.5      0.5406667     0.5923116 -0.03496485 150     0.044 *
## 10:     28.5      0.4966667     0.5699890 -0.06716888 150   0.0014 **
##     time  error.diff shapes
##  1:  1.5 -0.14651688     24
##  2:  4.5 -0.10328499     24
##  3:  7.5 -0.08186935     24
##  4: 10.5 -0.06779861     24
##  5: 13.5 -0.09318691     24
##  6: 16.5 -0.09807768     24
##  7: 19.5 -0.05423641     24
##  8: 22.5 -0.06446388     24
##  9: 25.5 -0.03496485     24
## 10: 28.5 -0.06716888     24

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n    pval
##  1:      1.5      0.1896552     0.1310662  0.014394476 29 0.81 :(
##  2:      4.5      0.1522727     0.1203089 -0.009091763 44 0.87 :(
##  3:      7.5      0.1864407     0.1442626  0.015290338 59 0.75 :(
##  4:     10.5      0.1702128     0.1384559 -0.011050247 47 0.87 :(
##  5:     13.5      0.1510204     0.1287708 -0.035862949 49  0.4 :(
##  6:     16.5      0.1625000     0.1478690 -0.036949324 64 0.34 :(
##  7:     19.5      0.1568627     0.1047740 -0.002704785 51 0.93 :(
##  8:     22.5      0.2367347     0.1313149  0.098777083 49 0.067 .
##  9:     25.5      0.2518519     0.1388075  0.103793162 54 0.029 *
## 10:     28.5      0.2192308     0.1316885  0.073792605 52 0.22 :(
##     time   error.diff shapes
##  1:  1.5  0.014394476     16
##  2:  4.5 -0.009091763     16
##  3:  7.5  0.015290338     16
##  4: 10.5 -0.011050247     16
##  5: 13.5 -0.035862949     16
##  6: 16.5 -0.036949324     16
##  7: 19.5 -0.002704785     16
##  8: 22.5  0.098777083     16
##  9: 25.5  0.103793162     24
## 10: 28.5  0.073792605     16

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n    pval
##  1:      1.5      0.3250000     0.4985511 -0.174369052 20  0.03 *
##  2:      4.5      0.5304348     0.5164721 -0.002160662 23 0.96 :(
##  3:      7.5      0.3666667     0.5212211 -0.155899714 21  0.07 .
##  4:     10.5      0.4689655     0.4998122 -0.038072242 29 0.52 :(
##  5:     13.5      0.3259259     0.4819058 -0.162603359 27 0.011 *
##  6:     16.5      0.3347826     0.4983878 -0.178759841 23 0.016 *
##  7:     19.5      0.4379310     0.4953200 -0.058047897 29 0.52 :(
##  8:     22.5      0.3400000     0.4806194 -0.173159924 30  0.04 *
##  9:     25.5      0.3333333     0.5100196 -0.181184503 15 0.035 *
## 10:     28.5      0.3833333     0.4795341 -0.105966628 24 0.11 :(
##     time   error.diff shapes
##  1:  1.5 -0.174369052     24
##  2:  4.5 -0.002160662     16
##  3:  7.5 -0.155899714     16
##  4: 10.5 -0.038072242     16
##  5: 13.5 -0.162603359     24
##  6: 16.5 -0.178759841     24
##  7: 19.5 -0.058047897     16
##  8: 22.5 -0.173159924     24
##  9: 25.5 -0.181184503     24
## 10: 28.5 -0.105966628     16

##     time.bin subj.diff.mean obj.diff.mean error.diff  n        pval
##  1:      1.5      0.6725490     0.9032837 -0.2276466 51 2.5e-06 ***
##  2:      4.5      0.6879518     0.9255749 -0.2238536 83 5.2e-10 ***
##  3:      7.5      0.7171429     0.8861503 -0.1683151 70   1e-05 ***
##  4:     10.5      0.7486486     0.9050947 -0.1457711 74 9.6e-05 ***
##  5:     13.5      0.7297297     0.9030341 -0.1663435 74 0.00017 ***
##  6:     16.5      0.7126984     0.8927203 -0.1729278 63 0.00012 ***
##  7:     19.5      0.7385714     0.8974839 -0.1612329 70   1e-04 ***
##  8:     22.5      0.7366197     0.9114922 -0.1693862 71 0.00016 ***
##  9:     25.5      0.7716049     0.9098869 -0.1173009 81   0.0022 **
## 10:     28.5      0.7283784     0.9073206 -0.1618660 74   2e-05 ***
##     time error.diff shapes
##  1:  1.5 -0.2276466     24
##  2:  4.5 -0.2238536     24
##  3:  7.5 -0.1683151     24
##  4: 10.5 -0.1457711     24
##  5: 13.5 -0.1663435     24
##  6: 16.5 -0.1729278     24
##  7: 19.5 -0.1612329     24
##  8: 22.5 -0.1693862     24
##  9: 25.5 -0.1173009     24
## 10: 28.5 -0.1618660     24

##     time.bin subj.diff.mean obj.diff.mean   error.diff   n        pval
##  1:      1.5      0.4355769     0.5969130 -0.167882862 104 3.2e-06 ***
##  2:      4.5      0.5089744     0.6297636 -0.133755664 156 3.6e-06 ***
##  3:      7.5      0.5102564     0.5544687 -0.055664136 156     0.036 *
##  4:     10.5      0.5224359     0.5229882 -0.002885828 156     0.89 :(
##  5:     13.5      0.5173077     0.5312208 -0.020469229 156     0.44 :(
##  6:     16.5      0.5102564     0.5008164  0.003037161 156     0.91 :(
##  7:     19.5      0.4576923     0.4456698  0.001732470 156     0.95 :(
##  8:     22.5      0.4211538     0.4198655 -0.005254933 156     0.84 :(
##  9:     25.5      0.4576923     0.3963862  0.067659240 156     0.015 *
## 10:     28.5      0.4435897     0.3637653  0.061888038 156     0.014 *
##     time   error.diff shapes
##  1:  1.5 -0.167882862     24
##  2:  4.5 -0.133755664     24
##  3:  7.5 -0.055664136     24
##  4: 10.5 -0.002885828     16
##  5: 13.5 -0.020469229     16
##  6: 16.5  0.003037161     16
##  7: 19.5  0.001732470     16
##  8: 22.5 -0.005254933     16
##  9: 25.5  0.067659240     24
## 10: 28.5  0.061888038     24

##     time.bin subj.diff.mean obj.diff.mean error.diff  n        pval
##  1:      1.5      0.2750000     0.1703706  0.1016483 28     0.053 .
##  2:      4.5      0.3000000     0.1381859  0.1648778 29     0.031 *
##  3:      7.5      0.3244898     0.1595726  0.1354454 49   0.0034 **
##  4:     10.5      0.3392857     0.1520208  0.1613247 56 3.1e-05 ***
##  5:     13.5      0.3584906     0.1600599  0.1879279 53 7.3e-05 ***
##  6:     16.5      0.3163934     0.1554278  0.1343604 61 0.00015 ***
##  7:     19.5      0.2694444     0.1311211  0.1325855 72   0.0028 **
##  8:     22.5      0.2408451     0.1190198  0.1159857 71     0.012 *
##  9:     25.5      0.3164557     0.1306707  0.1854950 79 3.7e-06 ***
## 10:     28.5      0.3183908     0.1222419  0.1919205 87 7.8e-06 ***
##     time error.diff shapes
##  1:  1.5  0.1016483     16
##  2:  4.5  0.1648778     24
##  3:  7.5  0.1354454     24
##  4: 10.5  0.1613247     24
##  5: 13.5  0.1879279     24
##  6: 16.5  0.1343604     24
##  7: 19.5  0.1325855     24
##  8: 22.5  0.1159857     24
##  9: 25.5  0.1854950     24
## 10: 28.5  0.1919205     24

## Warning: Removed 7 rows containing missing values (geom_errorbar).

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n    pval
##  1:      1.5      0.3681818     0.4997322 -0.130424640 22 0.046 *
##  2:      4.5      0.5160000     0.4989041  0.015221544 50 0.63 :(
##  3:      7.5      0.5714286     0.4833686  0.077957549 35  0.1 :(
##  4:     10.5      0.5461538     0.5149502  0.045706439 39 0.42 :(
##  5:     13.5      0.5439024     0.5233727  0.012310265 41 0.81 :(
##  6:     16.5      0.5631579     0.5000040  0.061074786 38 0.096 .
##  7:     19.5      0.5588235     0.4984335  0.054873807 34 0.22 :(
##  8:     22.5      0.5073171     0.4958407  0.025688540 41 0.57 :(
##  9:     25.5      0.5800000     0.4884663  0.092263010 35 0.023 *
## 10:     28.5      0.5064516     0.4870475  0.006024007 31 0.85 :(
##     time   error.diff shapes
##  1:  1.5 -0.130424640     24
##  2:  4.5  0.015221544     16
##  3:  7.5  0.077957549     16
##  4: 10.5  0.045706439     16
##  5: 13.5  0.012310265     16
##  6: 16.5  0.061074786     16
##  7: 19.5  0.054873807     16
##  8: 22.5  0.025688540     16
##  9: 25.5  0.092263010     24
## 10: 28.5  0.006024007     16

##     time.bin subj.diff.mean obj.diff.mean error.diff  n        pval
##  1:      1.5      0.5462963     0.8576753 -0.3151600 54 8.4e-09 ***
##  2:      4.5      0.5831169     0.8998770 -0.3363940 77 1.6e-12 ***
##  3:      7.5      0.6069444     0.8577800 -0.2492059 72 5.7e-10 ***
##  4:     10.5      0.6754098     0.8686874 -0.1942184 61   3e-06 ***
##  5:     13.5      0.6354839     0.8536933 -0.2151110 62   5e-07 ***
##  6:     16.5      0.6824561     0.8709845 -0.1841616 57 5.3e-06 ***
##  7:     19.5      0.6600000     0.8627407 -0.2014427 50   6e-06 ***
##  8:     22.5      0.6318182     0.8345259 -0.2072819 44 3.1e-05 ***
##  9:     25.5      0.6214286     0.8194509 -0.1991364 42 0.00012 ***
## 10:     28.5      0.6789474     0.8161546 -0.1202791 38   0.0049 **
##     time error.diff shapes
##  1:  1.5 -0.3151600     24
##  2:  4.5 -0.3363940     24
##  3:  7.5 -0.2492059     24
##  4: 10.5 -0.1942184     24
##  5: 13.5 -0.2151110     24
##  6: 16.5 -0.1841616     24
##  7: 19.5 -0.2014427     24
##  8: 22.5 -0.2072819     24
##  9: 25.5 -0.1991364     24
## 10: 28.5 -0.1202791     24

For all taks, per group

##     time.bin subj.diff.mean obj.diff.mean  error.diff  n        pval
##  1:      1.5      0.5611111     0.7831054 -0.23122829 54 1.1e-06 ***
##  2:      4.5      0.5790123     0.7787196 -0.21903626 81 7.5e-07 ***
##  3:      7.5      0.6246914     0.7724954 -0.16395951 81 3.6e-05 ***
##  4:     10.5      0.6506173     0.7303315 -0.08502097 81     0.023 *
##  5:     13.5      0.6419753     0.7550334 -0.13039377 81 0.00037 ***
##  6:     16.5      0.6283951     0.7254121 -0.10998601 81    0.003 **
##  7:     19.5      0.6456790     0.7183001 -0.07957346 81     0.011 *
##  8:     22.5      0.6320988     0.7195134 -0.09104759 81     0.024 *
##  9:     25.5      0.6123457     0.6832022 -0.05922553 81     0.13 :(
## 10:     28.5      0.6222222     0.6560278 -0.02387799 81      0.5 :(
##     time  error.diff shapes
##  1:  1.5 -0.23122829     24
##  2:  4.5 -0.21903626     24
##  3:  7.5 -0.16395951     24
##  4: 10.5 -0.08502097     24
##  5: 13.5 -0.13039377     24
##  6: 16.5 -0.10998601     24
##  7: 19.5 -0.07957346     24
##  8: 22.5 -0.09104759     24
##  9: 25.5 -0.05922553     16
## 10: 28.5 -0.02387799     16

##     time.bin subj.diff.mean obj.diff.mean    error.diff  n    pval
##  1:      1.5      0.4083333     0.5037926 -0.1084342463 36 0.12 :(
##  2:      4.5      0.5018519     0.5118848 -0.0005176423 54 0.99 :(
##  3:      7.5      0.4450980     0.4998803 -0.0503337019 51  0.2 :(
##  4:     10.5      0.5264151     0.4752785  0.0571322908 53 0.12 :(
##  5:     13.5      0.4627119     0.4791975 -0.0177220653 59 0.56 :(
##  6:     16.5      0.4563636     0.4955487 -0.0325529086 55  0.4 :(
##  7:     19.5      0.4527273     0.4981042 -0.0408845308 55 0.29 :(
##  8:     22.5      0.4464286     0.4779248 -0.0311130171 56 0.41 :(
##  9:     25.5      0.4562500     0.5136236 -0.0497880325 48 0.25 :(
## 10:     28.5      0.4866667     0.5094863 -0.0135613021 45 0.67 :(
##     time    error.diff shapes
##  1:  1.5 -0.1084342463     16
##  2:  4.5 -0.0005176423     16
##  3:  7.5 -0.0503337019     16
##  4: 10.5  0.0571322908     16
##  5: 13.5 -0.0177220653     16
##  6: 16.5 -0.0325529086     16
##  7: 19.5 -0.0408845308     16
##  8: 22.5 -0.0311130171     16
##  9: 25.5 -0.0497880325     16
## 10: 28.5 -0.0135613021     16

##     time.bin subj.diff.mean obj.diff.mean    error.diff   n      pval
##  1:      1.5      0.4179688     0.5035114 -0.0783724468 128 0.0049 **
##  2:      4.5      0.4369792     0.4789672 -0.0417134823 192   0.036 *
##  3:      7.5      0.4208333     0.4514087 -0.0282088189 192   0.16 :(
##  4:     10.5      0.4500000     0.4507039  0.0007470842 192   0.97 :(
##  5:     13.5      0.4057292     0.4266140 -0.0207845046 192   0.32 :(
##  6:     16.5      0.3958333     0.3985302 -0.0075410760 192   0.73 :(
##  7:     19.5      0.3927083     0.3878324 -0.0039587530 192   0.81 :(
##  8:     22.5      0.3697917     0.3737612 -0.0072105683 192   0.66 :(
##  9:     25.5      0.3994792     0.3674499  0.0277096775 192   0.12 :(
## 10:     28.5      0.3614583     0.3403232  0.0056352693 192   0.75 :(
##     time    error.diff shapes
##  1:  1.5 -0.0783724468     24
##  2:  4.5 -0.0417134823     24
##  3:  7.5 -0.0282088189     16
##  4: 10.5  0.0007470842     16
##  5: 13.5 -0.0207845046     16
##  6: 16.5 -0.0075410760     16
##  7: 19.5 -0.0039587530     16
##  8: 22.5 -0.0072105683     16
##  9: 25.5  0.0277096775     16
## 10: 28.5  0.0056352693     16

Per group, motor task

##     time.bin subj.diff.mean obj.diff.mean    error.diff  n    pval
##  1:      1.5      0.7000000     0.8422160 -0.1313282565 10 0.084 .
##  2:      4.5      0.7200000     0.8045511 -0.0795853830 15 0.49 :(
##  3:      7.5      0.6933333     0.7637929 -0.0692528749 15 0.25 :(
##  4:     10.5      0.7200000     0.7894410 -0.0625540247 15 0.36 :(
##  5:     13.5      0.7000000     0.8006171 -0.1084499094 15 0.055 .
##  6:     16.5      0.7200000     0.7661172 -0.0140493178 15  0.8 :(
##  7:     19.5      0.7466667     0.7396280  0.0120888700 15  0.8 :(
##  8:     22.5      0.7333333     0.7489324 -0.0006995672 15    1 :(
##  9:     25.5      0.7533333     0.8163298 -0.0314486693 15  0.6 :(
## 10:     28.5      0.6866667     0.7440259 -0.0101905183 15 0.85 :(
##     time    error.diff shapes
##  1:  1.5 -0.1313282565     16
##  2:  4.5 -0.0795853830     16
##  3:  7.5 -0.0692528749     16
##  4: 10.5 -0.0625540247     16
##  5: 13.5 -0.1084499094     16
##  6: 16.5 -0.0140493178     16
##  7: 19.5  0.0120888700     16
##  8: 22.5 -0.0006995672     16
##  9: 25.5 -0.0314486693     16
## 10: 28.5 -0.0101905183     16

##     time.bin subj.diff.mean obj.diff.mean  error.diff  n    pval
##  1:      1.5      0.4750000     0.5183516 -0.03087319 20  0.7 :(
##  2:      4.5      0.4718750     0.5208957 -0.04122231 32 0.42 :(
##  3:      7.5      0.4151515     0.4974840 -0.07427876 33 0.11 :(
##  4:     10.5      0.4903226     0.4619969  0.02981484 31 0.44 :(
##  5:     13.5      0.4823529     0.4705545  0.01736858 34 0.67 :(
##  6:     16.5      0.4696970     0.5043588 -0.03184720 33 0.55 :(
##  7:     19.5      0.4225806     0.5088668 -0.10175151 31 0.041 *
##  8:     22.5      0.4451613     0.4735961 -0.03958767 31 0.54 :(
##  9:     25.5      0.4437500     0.5133883 -0.06412644 32 0.19 :(
## 10:     28.5      0.4620690     0.5063094 -0.03759442 29 0.45 :(
##     time  error.diff shapes
##  1:  1.5 -0.03087319     16
##  2:  4.5 -0.04122231     16
##  3:  7.5 -0.07427876     16
##  4: 10.5  0.02981484     16
##  5: 13.5  0.01736858     16
##  6: 16.5 -0.03184720     16
##  7: 19.5 -0.10175151     24
##  8: 22.5 -0.03958767     16
##  9: 25.5 -0.06412644     16
## 10: 28.5 -0.03759442     16

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n    pval
##  1:      1.5      0.5238095     0.5010468  0.029289622 42 0.44 :(
##  2:      4.5      0.4777778     0.4761135  0.006623743 63 0.82 :(
##  3:      7.5      0.4507937     0.4585390 -0.004803129 63  0.9 :(
##  4:     10.5      0.5111111     0.4440686  0.079755085 63 0.014 *
##  5:     13.5      0.4349206     0.4202938  0.019074304 63 0.57 :(
##  6:     16.5      0.4809524     0.4449609  0.036494116 63 0.21 :(
##  7:     19.5      0.4650794     0.4547299  0.003733181 63 0.89 :(
##  8:     22.5      0.4444444     0.4137030  0.029021770 63 0.27 :(
##  9:     25.5      0.4079365     0.3720518  0.034671878 63 0.19 :(
## 10:     28.5      0.3825397     0.3393145  0.035270385 63 0.18 :(
##     time   error.diff shapes
##  1:  1.5  0.029289622     16
##  2:  4.5  0.006623743     16
##  3:  7.5 -0.004803129     16
##  4: 10.5  0.079755085     24
##  5: 13.5  0.019074304     16
##  6: 16.5  0.036494116     16
##  7: 19.5  0.003733181     16
##  8: 22.5  0.029021770     16
##  9: 25.5  0.034671878     16
## 10: 28.5  0.035270385     16

Per group, sensory task

##     time.bin subj.diff.mean obj.diff.mean  error.diff  n      pval
##  1:      1.5      0.5200000     0.6532009 -0.15481410 20   0.064 .
##  2:      4.5      0.5233333     0.6798318 -0.16011025 30 0.0099 **
##  3:      7.5      0.5600000     0.7258520 -0.17698999 30 0.0032 **
##  4:     10.5      0.6166667     0.7095321 -0.09775791 30   0.096 .
##  5:     13.5      0.6300000     0.7392049 -0.10048434 30   0.045 *
##  6:     16.5      0.5033333     0.6342894 -0.17482129 30    0.02 *
##  7:     19.5      0.5666667     0.6736744 -0.14656607 30   0.061 .
##  8:     22.5      0.6766667     0.7269536 -0.04503328 30   0.53 :(
##  9:     25.5      0.5200000     0.6353846 -0.10395476 30    0.08 .
## 10:     28.5      0.5400000     0.6179671 -0.06264246 30   0.31 :(
##     time  error.diff shapes
##  1:  1.5 -0.15481410     16
##  2:  4.5 -0.16011025     24
##  3:  7.5 -0.17698999     24
##  4: 10.5 -0.09775791     16
##  5: 13.5 -0.10048434     24
##  6: 16.5 -0.17482129     24
##  7: 19.5 -0.14656607     16
##  8: 22.5 -0.04503328     16
##  9: 25.5 -0.10395476     16
## 10: 28.5 -0.06264246     16

##     time.bin subj.diff.mean obj.diff.mean  error.diff  n    pval
##  1:      1.5      0.3750000     0.4494773 -0.08412785  8 0.55 :(
##  2:      4.5      0.5714286     0.4978879  0.07602487  7 0.47 :(
##  3:      7.5      0.4666667     0.5261586 -0.05251118  9 0.65 :(
##  4:     10.5      0.5333333     0.5140517  0.03447164 15 0.89 :(
##  5:     13.5      0.3714286     0.4603739 -0.11410615 14 0.22 :(
##  6:     16.5      0.2800000     0.4574613 -0.17916165 10 0.23 :(
##  7:     19.5      0.4733333     0.4979102 -0.00987953 15 0.98 :(
##  8:     22.5      0.3764706     0.4681605 -0.13208832 17 0.33 :(
##  9:     25.5      0.4125000     0.5357926 -0.12625470  8 0.46 :(
## 10:     28.5      0.4857143     0.5175172 -0.02929477  7 0.94 :(
##     time  error.diff shapes
##  1:  1.5 -0.08412785     16
##  2:  4.5  0.07602487     16
##  3:  7.5 -0.05251118     16
##  4: 10.5  0.03447164     16
##  5: 13.5 -0.11410615     16
##  6: 16.5 -0.17916165     16
##  7: 19.5 -0.00987953     16
##  8: 22.5 -0.13208832     16
##  9: 25.5 -0.12625470     16
## 10: 28.5 -0.02929477     16

## Warning: Removed 7 rows containing missing values (geom_errorbar).

##     time.bin subj.diff.mean obj.diff.mean  error.diff  n        pval
##  1:      1.5      0.3500000     0.5485343 -0.21270071 34   9e-04 ***
##  2:      4.5      0.3745098     0.5092188 -0.11705556 51    0.001 **
##  3:      7.5      0.3843137     0.4752661 -0.07499866 51     0.022 *
##  4:     10.5      0.4313725     0.5005706 -0.07577894 51     0.014 *
##  5:     13.5      0.3333333     0.4748447 -0.13845000 51 0.00028 ***
##  6:     16.5      0.3000000     0.4402784 -0.13195159 51   1e-04 ***
##  7:     19.5      0.3745098     0.4807634 -0.08176183 51    0.001 **
##  8:     22.5      0.3843137     0.4979837 -0.09803991 51     0.014 *
##  9:     25.5      0.4764706     0.5461227 -0.04087166 51     0.13 :(
## 10:     28.5      0.3784314     0.5097181 -0.11274030 51   5e-04 ***
##     time  error.diff shapes
##  1:  1.5 -0.21270071     24
##  2:  4.5 -0.11705556     24
##  3:  7.5 -0.07499866     24
##  4: 10.5 -0.07577894     24
##  5: 13.5 -0.13845000     24
##  6: 16.5 -0.13195159     24
##  7: 19.5 -0.08176183     24
##  8: 22.5 -0.09803991     24
##  9: 25.5 -0.04087166     16
## 10: 28.5 -0.11274030     24

Per group, logical task

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n        pval
##  1:      1.5      0.5375000     0.8667296 -0.336223194 24 8.3e-07 ***
##  2:      4.5      0.5666667     0.8503630 -0.300166011 36 8.1e-06 ***
##  3:      7.5      0.6500000     0.8149910 -0.191351305 36   0.0067 **
##  4:     10.5      0.6500000     0.7230354 -0.075959113 36     0.21 :(
##  5:     13.5      0.6277778     0.7492306 -0.168314679 36     0.043 *
##  6:     16.5      0.6944444     0.7843873 -0.103751078 36      0.1 :(
##  7:     19.5      0.6694444     0.7466016 -0.071855795 36     0.088 .
##  8:     22.5      0.5527778     0.7010553 -0.155156364 36     0.017 *
##  9:     25.5      0.6305556     0.6675804 -0.011808735 36     0.88 :(
## 10:     28.5      0.6638889     0.6510792  0.008180296 36     0.87 :(
##     time   error.diff shapes
##  1:  1.5 -0.336223194     24
##  2:  4.5 -0.300166011     24
##  3:  7.5 -0.191351305     24
##  4: 10.5 -0.075959113     16
##  5: 13.5 -0.168314679     24
##  6: 16.5 -0.103751078     16
##  7: 19.5 -0.071855795     16
##  8: 22.5 -0.155156364     24
##  9: 25.5 -0.011808735     16
## 10: 28.5  0.008180296     16

## Warning: Removed 2 rows containing missing values (geom_errorbar).

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n    pval
##  1:      1.5      0.2750000     0.5217103 -0.229283586  8 0.023 *
##  2:      4.5      0.5333333     0.4991934  0.047762357 15 0.52 :(
##  3:      7.5      0.5333333     0.4823887  0.057073281  9 0.82 :(
##  4:     10.5      0.6714286     0.4510115  0.190422675  7 0.016 *
##  5:     13.5      0.5181818     0.5298697 -0.006964140 11 0.58 :(
##  6:     16.5      0.5666667     0.5030605  0.026891236 12 0.52 :(
##  7:     19.5      0.5222222     0.4613564  0.086019831  9 0.57 :(
##  8:     22.5      0.6000000     0.5154471  0.093656413  8 0.31 :(
##  9:     25.5      0.5500000     0.4923959  0.048797391  8  0.2 :(
## 10:     28.5      0.5666667     0.5134768  0.007249275  9 0.91 :(
##     time   error.diff shapes
##  1:  1.5 -0.229283586     24
##  2:  4.5  0.047762357     16
##  3:  7.5  0.057073281     16
##  4: 10.5  0.190422675     24
##  5: 13.5 -0.006964140     16
##  6: 16.5  0.026891236     16
##  7: 19.5  0.086019831     16
##  8: 22.5  0.093656413     16
##  9: 25.5  0.048797391     16
## 10: 28.5  0.007249275     16

## Warning: Removed 6 rows containing missing values (geom_errorbar).

##     time.bin subj.diff.mean obj.diff.mean   error.diff  n    pval
##  1:      1.5      0.3769231     0.4760639 -0.102437219 52 0.042 *
##  2:      4.5      0.4448718     0.4614922 -0.027759149 78 0.44 :(
##  3:      7.5      0.4205128     0.4300504 -0.017443018 78 0.62 :(
##  4:     10.5      0.4128205     0.4234581 -0.008719531 78 0.81 :(
##  5:     13.5      0.4294872     0.4001833  0.034200208 78 0.44 :(
##  6:     16.5      0.3897436     0.3337317  0.052227726 78 0.13 :(
##  7:     19.5      0.3461538     0.2730373  0.067476620 78 0.073 .
##  8:     22.5      0.3000000     0.2602781  0.014479723 78 0.59 :(
##  9:     25.5      0.3423077     0.2469083  0.092629303 78 0.011 *
## 10:     28.5      0.3333333     0.2303798  0.075981671 78 0.048 *
##     time   error.diff shapes
##  1:  1.5 -0.102437219     24
##  2:  4.5 -0.027759149     16
##  3:  7.5 -0.017443018     16
##  4: 10.5 -0.008719531     16
##  5: 13.5  0.034200208     16
##  6: 16.5  0.052227726     16
##  7: 19.5  0.067476620     16
##  8: 22.5  0.014479723     16
##  9: 25.5  0.092629303     24
## 10: 28.5  0.075981671     24

Link between d(t-1) and error

## Warning: Removed 8 rows containing missing values (geom_path).

## Warning: Removed 3 rows containing missing values (geom_path).

## Warning: Removed 16 rows containing missing values (geom_path).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 5.7749, p-value = 7.698e-09
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.07064766 
## 
## [1] "DT 0.071 7.7e-09 ***"

## Résultat test Kendall erreur basée sur mise avec confiance estimée : 0.071 7.7e-09 ***

## 
##  F test to compare two variances
## 
## data:  pas.confiant and super.confiant
## F = 1.6455, num df = 540, denom df = 249, p-value = 9.585e-06
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
##  1.324565 2.026924
## sample estimates:
## ratio of variances 
##           1.645473

## SD des pas confiants : 0.3291113

## SD des super confiants : 0.2565649

## Warning: Removed 1 rows containing missing values (geom_path).

## Warning: Removed 5 rows containing missing values (geom_path).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.4124, p-value = 0.1578
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.02562088

## Résultat test Kendall erreur basée sur mise avec confiance estimée : 0.026 0.16 :(

## 
##  F test to compare two variances
## 
## data:  pas.confiant and super.confiant
## F = 1.6083, num df = 374, denom df = 224, p-value = 0.0001088
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
##  1.267442 2.026607
## sample estimates:
## ratio of variances 
##           1.608304

## SD des pas confiants : 0.2912976

## SD des super confiants : 0.2296957

## Warning: Removed 2 rows containing missing values (geom_path).

## Warning: Removed 10 rows containing missing values (geom_path).

## Warning: Removed 7 rows containing missing values (geom_path).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.0486, p-value = 0.2944
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.01847355

## 
##  F test to compare two variances
## 
## data:  pas.confiant and super.confiant
## F = 0.85648, num df = 478, denom df = 115, p-value = 0.2713
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
##  0.6332665 1.1288219
## sample estimates:
## ratio of variances 
##          0.8564843

## SD des pas confiants : 0.2568515

## SD des super confiants : 0.277538

## Résultat test Kendall erreur basée sur mise avec confiance estimée : 0.018 0.29 :(

## Warning: Removed 28 rows containing missing values (geom_path).

## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?

## Warning: Removed 8 rows containing missing values (geom_path).

## Warning: Removed 6 rows containing missing values (geom_path).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 3.9056, p-value = 9.399e-05
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.06739139 
## 
## [1] "DTL 0.067 9.4e-05 ***"

## Résultat test Kendall erreur basée sur mise avec confiance estimée : 0.067 9.4e-05 ***

## 
##  F test to compare two variances
## 
## data:  pas.confiant and super.confiant
## F = 1.7176, num df = 478, denom df = 339, p-value = 1.39e-07
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
##  1.407941 2.088275
## sample estimates:
## ratio of variances 
##           1.717565

## SD des pas confiants : 0.3744891

## SD des super confiants : 0.2857475

Subjective difficulty and play habits

Playing video game in general and subjective difficulty error

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -1.9512, p-value = 0.05103
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.1244062 
## 
## [1] "pvg.on.error -0.12 0.051 ."

Playing board game in general and subjective difficulty error

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -2.611, p-value = 0.009028
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.1640952 
## 
## [1] "pbg.on.error -0.16 0.009 **"

In game level and subjective difficulty error

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.4956, p-value = 0.1348
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.08314103

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## T = 516, p-value = 0.6615
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.0453284

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.1962, p-value = 0.2316
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.1167347

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.7676, p-value = 0.07713
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.1689291 
## 
## [1] "niveau.group.on.error.l 0.17 0.077 ."

Sex and subjective difficulty error

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 3.4092, p-value = 0.0006514
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.2309816 
## 
## [1] "sexe.on.error 0.23 0.00065 ***"

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.8377, p-value = 0.06611
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.2235683 
## 
## [1] "sexe.on.error.m 0.22 0.066 ."

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 2.1421, p-value = 0.03218
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##       tau 
## 0.2523479 
## 
## [1] "sexe.on.error.s 0.25 0.032 *"

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 1.9042, p-value = 0.05688
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##      tau 
## 0.219795 
## 
## [1] "sexe.on.error.l 0.22 0.057 ."

## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  B and A
## W = 3351, p-value = 0.0006562
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.01884107 0.09421998
## sample estimates:
## difference in location 
##              0.0580818 
## 
## [1] "sexe.on.error.2 0.058 0.00066 *** mean(A): -0.057 mean(B): -0.00063"

## 
##  Wilcoxon rank sum test
## 
## data:  B and A
## W = 338, p-value = 0.06742
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.002139502  0.112594328
## sample estimates:
## difference in location 
##             0.05082362 
## 
## [1] "sexe.on.error.m.2 0.051 0.067 . mean(A): -0.052 mean(B): 0.0015"

## 
##  Wilcoxon rank sum test
## 
## data:  B and A
## W = 375, p-value = 0.032
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.004691109 0.132198686
## sample estimates:
## difference in location 
##             0.06809898 
## 
## [1] "sexe.on.error.s.2 0.068 0.032 * mean(A): -0.058 mean(B): 0.008"

## 
##  Wilcoxon rank sum test
## 
## data:  B and A
## W = 405, p-value = 0.05764
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.001446698  0.111180497
## sample estimates:
## difference in location 
##             0.05042229 
## 
## [1] "sexe.on.error.l.2 0.05 0.058 . mean(A): -0.061 mean(B): -0.01"

Risk aversion and subjective difficulty error

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 0.69771, p-value = 0.4854
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.04215397

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -0.43467, p-value = 0.6638
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##         tau 
## -0.04748814

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 0.73768, p-value = 0.4607
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.07731606

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = 0.85186, p-value = 0.3943
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## 0.08786374

Self efficacy and subjective difficulty error

## Warning: Removed 72 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -3.3268, p-value = 0.0008786
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.2704897 
## 
## [1] "self.eff.on.error -0.27 0.00088 ***"

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning: Removed 23 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -1.8964, p-value = 0.0579
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.2826236 
## 
## [1] "self.eff.on.error -0.28 0.058 ."

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning in cor.test.default(Y, X, method = "kendall"): Removed 23 rows
## containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -1.7201, p-value = 0.08542
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.2402101 
## 
## [1] "self.eff.on.error -0.24 0.085 ."

## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties

## Warning: Removed 26 rows containing missing values (geom_point).

## 
##  Kendall's rank correlation tau
## 
## data:  Y and X
## z = -2.0192, p-value = 0.04346
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
##        tau 
## -0.2880916 
## 
## [1] "self.eff.on.error -0.29 0.043 *"